The internet is a powerful tool for content providers to reach out to a large audience. The internet provides powerful targeted content provision methods such as contextual targeting, behavioral targeting, lifestyle targeting, demographic targeting, geographic targeting and the like. Much like other media, the internet content provision industry relies on a unique user statistic to measure the true size of the audience of a website. The unique user statistic is one describing a unit of traffic to a website in a predefined time frame, for instance one week, one month, and so forth.
One way to measure the unique user statistic is through use of internet usage surveys such as those conducted by comScore Inc., and Nielsen Online. Because such surveys use panels of web users to gather data and then extrapolate, the results are estimates. Typically, surveys are restricted to smaller geographical areas, such as a single country. Therefore, surveys may not present an accurate statistic for international audiences. Particularly for websites and web applications having a small target audience, and small geographical areas, panel data is sparsely available, or not available at all. This makes the extrapolated and estimated unique user statistic unreliable.
Another method to measure the unique user statistic is through the use of registration. Users may be required to register for web sites, and may be granted access to the website only by signing-in. However, users may not always register for web sites, and may instead opt to use another web site not requiring registration. Further, many users may create several user accounts. For instance, users may create different user accounts for business use and for personal use.
Yet another method to measure the unique user statistic is by the use of cookies. A web server hosting the web site may place a cookie on the client computer of each visitor. The web server may then count the number of unique users by checking for the cookie each time a user visits the web site. However, users may often clear their cookies. This may result in inflated statistics. Further, multiple users may often share client computers to access the internet. In such a scenario, multiple users may use the same cookie, thus resulting in deflated statistics.
Therefore, there is a need for a method for addressing these and other shortcomings associated with counting the number of network users.